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BeamECOC: A local search for the optimization of the ECOC matrix

Zor, Cemre, Yanikoglu, Berrin, Merdivan, Erinc, Windeatt, Terry, Kittler, Josef and Alpaydin, Ethem (2017) BeamECOC: A local search for the optimization of the ECOC matrix In: 2016 23rd International Conference on Pattern Recognition (ICPR), 4 - 8 December 2016, Cancun, Mexico.

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Error Correcting Output Coding (ECOC) is a multi- class classification technique in which multiple binary classifiers are trained according to a preset code matrix such that each one learns a separate dichotomy of the classes. While ECOC is one of the best solutions for multi-class problems, one issue which makes it suboptimal is that the training of the base classifiers is done independently of the generation of the code matrix. In this paper, we propose to modify a given ECOC matrix to improve its performance by reducing this decoupling. The proposed algorithm uses beam search to iteratively modify the original matrix, using validation accuracy as a guide. It does not involve further training of the classifiers and can be applied to any ECOC matrix. We evaluate the accuracy of the proposed algorithm (BeamE- COC) using 10-fold cross-validation experiments on 6 UCI datasets, using random code matrices of different sizes, and base classifiers of different strengths. Compared to the random ECOC approach, BeamECOC increases the average cross-validation accuracy in 83 : 3% of the experimental settings involving all datasets, and gives better results than the state-of-the-art in 75% of the scenarios. By employing BeamECOC, it is also possible to reduce the number of columns of a random matrix down to 13% and still obtain comparable or even better results at times.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Yanikoglu, Berrin
Merdivan, Erinc
Alpaydin, Ethem
Date : 24 April 2017
Funders : EPSRC
DOI : 10.1109/ICPR.2016.7899633
Copyright Disclaimer : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : ECOC, Error correcting output codes, ensemble, learning, beam search
Depositing User : Melanie Hughes
Date Deposited : 02 Aug 2018 09:04
Last Modified : 11 Dec 2018 11:24

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